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Generalized Composite Kernel Framework for Hyperspectral Image Classification.

, , , , и . IEEE Trans. Geosci. Remote. Sens., 51 (9): 4816-4829 (2013)

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Humberto Jorge José

Nadine José Gonzalez

Manjula Dias-Hargarter

Marcelo Dias

José Baena

 

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Parallel implementation of vertex component analysis for hyperspectral endmember extraction., , , , и . IGARSS, стр. 4078-4081. IEEE, (2012)Learning dependent sources using mixtures of Dirichlet: Applications on hyperspectral unmixing., и . WHISPERS, стр. 1-5. IEEE, (2009)Fast Hyperspectral Image Denoising and Inpainting Based on Low-Rank and Sparse Representations., и . IEEE J Sel. Topics in Appl. Earth Observ. and Remote Sensing, 11 (3): 730-742 (2018)Linear Spectral Unmixing via Matrix Factorization: Identifiability Criteria for Sparse Abundances., и . IGARSS, стр. 6155-6158. IEEE, (2018)Total Variation-Based Image Deconvolution: a Majorization-Minimization Approach., , и . ICASSP (2), стр. 861-864. IEEE, (2006)Semisupervised Self-Learning for Hyperspectral Image Classification., , , , , и . IEEE Trans. Geosci. Remote. Sens., 51 (7-1): 4032-4044 (2013)Generalized Composite Kernel Framework for Hyperspectral Image Classification., , , , и . IEEE Trans. Geosci. Remote. Sens., 51 (9): 4816-4829 (2013)Self-Dictionary Sparse Regression for Hyperspectral Unmixing: Greedy Pursuit and Pure Pixel Search Are Related., , , и . IEEE J. Sel. Top. Signal Process., 9 (6): 1128-1141 (2015)Effect of Denoising in Band Selection for Regression Tasks in Hyperspectral Datasets., , , , и . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 6 (2-2): 473-481 (2013)Convex formulation for hyperspectral image classification with superpixels., , , , и . IGARSS, стр. 3294-3297. IEEE, (2016)